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Questions Old‐fields and their succession often played crucial role in dynamics of species‐rich semi‐natural grasslands. Our objective was to assess whether colonization of old‐fields by grassland species is limited by the availability of seeds, dispersal abilities, habitat requirements of the species or biotic interactions. In particular, we asked following questions: (1) What are the main constrains limiting frequency of grassland species in old‐fields? (2) Is frequency in source habitat (grasslands) and target habitat (old‐fields) limited by the same factors/processes? And (3) how the results and their interpretation change after considering species phylogeny? Location Old‐fields and grasslands in northern Bohemia, Czech Republic, Europe. Methods Frequency in old‐fields and grasslands of 29 plant species was related to a set of species characteristics representing source, dispersal, abiotic and biotic limitation using phylogenetic regression. Results Species frequency in old‐fields was significantly correlated with frequency in grasslands. In general, habitat (biotic and abiotic) limitation was more important for frequency in both habitat types without phylogenetic correction. Specifically, frequency in both habitat types was mostly limited by soil preference and in grasslands also by niche width. Old‐fields were relatively more colonized by species with better competitiveness. Phylogenetic signal was not detected during phylogenetic regression. Conclusions To preserve high diversity in grasslands, the effort should be directed towards maintenance of soil quality (minimize the use of fertilizers, pesticides and heavy machinery). Colonization of old‐fields could be enhanced by reduction of competitive species by introduction of traditional management (e.g., mowing or grazing). What are the main constrains limiting frequency of grassland species in source habitat (grasslands) and target habitat (old‐fields)? A set of species characteristics was used to distinguish between source, dispersal, abiotic and biotic limitation. Habitat (biotic and abiotic) limitation was more important for frequency in both habitat types. Old‐fields were relatively more colonized by species with better competitiveness.

Genetically engineered mouse models of cancer can be used to filter genome‐wide expression datasets generated from human tumours and to identify gene expression alterations that are functionally important to cancer development and progression. In this study, we have generated RNAseq data from tumours arising in two established mouse models of prostate cancer, PB‐Cre/Pten loxP/loxP and p53 loxP/lox P Rb loxP/loxP , and integrated this with published human prostate cancer expression data to pinpoint cancer‐associated gene expression changes that are conserved between the two species. To identify potential therapeutic targets, we then filtered this information for genes that are either known or predicted to be druggable. Using this approach, we revealed a functional role for the kinase MELK as a driver and potential therapeutic target in prostate cancer. We found that MELK expression was required for cell survival, affected the expression of genes associated with prostate cancer progression and was associated with biochemical recurrence. Synopsis Genetically engineered mouse models (GEMM) of human cancers can be used as “biological filters” to identify genes that are important to cancer development and prioritise potential therapeutic targets. The example of MELK in prostate cancer. Comparisons of high‐throughput sequencing data from two GEMM of prostate cancer with human prostate cancer gene expression data revealed that human and murine tumours share common gene expression alterations. Integration of human and murine gene expression data was used to identify potential therapeutic targets in prostate cancer, including the protein kinase MELK. MELK is overexpressed in prostate cancer and associated with poor prognosis. Silencing of MELK or treatment with an inhibitor targeting MELK resulted in induction of apoptosis in prostate cancer cells in vitro and in vivo . Graphical Abstract Genetically engineered mouse models (GEMM) of human cancers can be used as “biological filters” to identify genes that are important to cancer development and prioritise potential therapeutic targets. The example of MELK in prostate cancer.

Worldwide, donkeys (Equus asinus) are valued for their meat and milk, and in China also for the medical value of their skin. Physiological characteristics are key to the donkey's adaptability, including their digestive, respiratory, and reproductive systems, which enable them to survive and work in a variety of environments. However, the understanding of donkey physiological characteristics at the cellular level remains poor. Thus, single‐cell transcriptome sequencing is used to construct a detailed transcriptional atlas based on 20 tissues from the Dezhou donkey (in total 84 cell types and 275 050 high quality cells) to perform an in‐depth investigation of molecular physiology. Cross‐species and cross‐tissue comparative analyses reveal SOX10 to be an evolutionally conserved regulon in oligodendrocytes and illuminate the distinctive transcriptional patterns of donkey sebocytes. Moreover, through multispecies skin metabolomics, highly abundant, species‐specific metabolites in donkey skin are identified, such as arachidonic acid and gamma‐glutamylcysteine, and the pivotal role of sebocytes in donkey skin metabolism is highlighted. In summary, this work offers new insights into the unique metabolic patterns of donkey skin and provides a valuable resource for the conservation of donkey germplasm and the advancement of selective breeding programs. In this study, a comprehensive single‐cell transcriptome atlas of the Dezhou donkey, encompassing 20 tissues and 275 050 cells, is constructed. Through cross‐species and cross‐tissue analyses, distinct transcriptional patterns in donkey sebocytes are identified. Furthermore, multispecies skin metabolomics reveal species‐specific metabolites, emphasizing the critical role of sebocytes in shaping the unique metabolic profile of donkey skin.

The yak, an ideal model for studying high‐altitude hypoxia adaptation, possesses unique gastrointestinal tract (GIT) adaptability. However, understanding of cellular‐level mechanisms underlying host‐metabolite‐microbe within GIT that are crucial for growth in extreme environments remains significantly limited. Therefore, this study constructs the first comprehensive multi‐tissue cellular atlas of the yak GIT, encompassing 54 distinct cell types. Cross‐species and cross‐tissue comparative analyses combined with large‐scale population genetic data identify HNF4A and SREBF2 as GIT‐specific transcription factors targeting the key gene MYO6, revealing unique transcriptional patterns and the significant influence of epithelial cells on yak body weight in GIT. Alongside the characterization of microorganisms and metabolites along the GIT, the important microorganism Bacillus infection has cell‐type specificity, and affects the accumulation of key products such as Succinate and lactic acid through the interaction between different epithelial cell metabolic activities and microorganisms and the communication between different cell types (key receptors SLC27A5, PPARA), thereby affecting glycolysis and TCA cycle and other processes to strengthen the adaptability of yak GIT in extreme environments. This work provides novel insights into the unique gastrointestinal adaptations of yaks to extreme environments and holds significant implications for understanding precision breeding in yaks and mammal gastrointestinal responses to hypoxia. In this study, a single‐cell atlas of 117,019 yak gastrointestinal cells across 54 subtypes identified HNF4A and SREBF2 as key transcription factors targeting MYO6 gene. Cross‐species and multi‐omics analyses reveals epithelial cells as key regulators that, through interactions with microbes, particularly Bacillus, facilitate flexible energy supply and glycogen storage to cope with the challenges of yak growth under high‐altitude conditions.

The lack of natural aging‐inducing Alzheimer's disease (AD) model presents a significant gap in the current preclinical research. Here, we identified a unique cohort of 10 naturally aging tree shrews (TSs) displaying distinct Alzheimer's‐like pathology (ALP) from a population of 324, thereby establishing a novel model that closely mirrors human AD progression. Using single‐nucleus RNA sequencing, we generated a comprehensive transcriptome atlas, revealing the cellular diversity and gene expression changes underlying AD pathology in aged TSs. Particularly, distinct differentiation trajectories of neural progenitor cells were highly associated with AD pathology. Intriguingly, cross‐species comparisons among humans, TSs, monkeys, and mice highlighted a greater cellular homogeneity of TSs to primates and humans than to mice. Our extended cross‐species analysis by including a direct comparison between human and TS hippocampal tissue under AD conditions uncovered conserved cell types, enriched synaptic biological processes, and elevated excitatory/inhibitory imbalance across species. Cell–cell communication analysis unveiled parallel patterns between AD human and ALP TSs, with both showing reduced interaction strength and quantity across most cell types. Overall, our study provides rich, high‐resolution resources on the cellular and molecular landscape of the ALP TS hippocampus, reinforcing the utility of TSs as a robust model for AD research. We present a novel Alzheimer's disease (AD) model using naturally aging tree shrews (TSs) that exhibit Alzheimer's‐like pathology (ALP), offering unique insights into human AD progression. Through single‐nucleus RNA sequencing, we mapped the hippocampal transcriptome, revealing key neural progenitor cell differentiation trajectories linked to AD. Cross‐species comparisons demonstrated greater cellular and genetic similarities between TSs and primates than mice, highlighting conserved cell types, synaptic processes, and excitatory/inhibitory imbalances. Cell–cell communication patterns mirrored those in AD human tissue, underscoring the value of TSs as a translational model for AD research.

Token reinforcement procedures and concepts are reviewed and discussed in relation to general principles of behavior. The paper is divided into four main parts. Part I reviews and discusses previous research on token systems in relation to common behavioral functions—reinforcement, temporal organization, antecedent stimulus functions, and aversive control—emphasizing both the continuities with other contingencies and the distinctive features of token systems. Part II describes the role of token procedures in the symmetrical law of effect, the view that reinforcers (gains) and punishers (losses) can be measured in conceptually analogous terms. Part III considers the utility of token reinforcement procedures in cross‐species analysis of behavior more generally, showing how token procedures can be used to bridge the methodological gulf separating research with humans from that with other animals. Part IV discusses the relevance of token systems to the field of behavioral economics. Token systems have the potential to significantly advance research and theory in behavioral economics, permitting both a more refined analysis of the costs and benefits underlying standard economic models, and a common currency more akin to human monetary systems. Some implications for applied research and for broader theoretical integration across disciplines will also be considered.

Background CTCF binding contributes to the establishment of a higher-order genome structure by demarcating the boundaries of large-scale topologically associating domains (TADs). However, despite the importance and conservation of TADs, the role of CTCF binding in their evolution and stability remains elusive. Results We carry out an experimental and computational study that exploits the natural genetic variation across five closely related species to assess how CTCF binding patterns stably fixed by evolution in each species contribute to the establishment and evolutionary dynamics of TAD boundaries. We perform CTCF ChIP-seq in multiple mouse species to create genome-wide binding profiles and associate them with TAD boundaries. Our analyses reveal that CTCF binding is maintained at TAD boundaries by a balance of selective constraints and dynamic evolutionary processes. Regardless of their conservation across species, CTCF binding sites at TAD boundaries are subject to stronger sequence and functional constraints compared to other CTCF sites. TAD boundaries frequently harbor dynamically evolving clusters containing both evolutionarily old and young CTCF sites as a result of the repeated acquisition of new species-specific sites close to conserved ones. The overwhelming majority of clustered CTCF sites colocalize with cohesin and are significantly closer to gene transcription start sites than nonclustered CTCF sites, suggesting that CTCF clusters particularly contribute to cohesin stabilization and transcriptional regulation. Conclusions Dynamic conservation of CTCF site clusters is an apparently important feature of CTCF binding evolution that is critical to the functional stability of a higher-order chromatin structure.

Seed size is widely held to exert an important influence over plant establishment, but while large seeds are often assumed to be at an advantage in nutrient-limited conditions, there is in fact, little consistent evidence to support this hypothesis. Here, we examined the interspecific relationship between seedling growth and seed size for Australian and British Fabaceae species in nutrient solutions deficient in nitrogen, phosphorus, potassium or all nutrients combined (distilled water). The British species showed no consistent link between mean seed mass and seedling growth in nutrient-limited conditions. By contrast, all four nutrient-deficient treatments yielded a significant relationship for the Australian species. Linear regression showed that growth under balanced nutrient conditions was positively associated with growth without nutrients, although in fewer cases for the British species. We suggest that habitat-specific differences in regeneration conditions and/or evolutionary history may influence the role that seed size plays in dictating how seedlings of different species respond to nutrient shortage. We recommend caution in attempts to link traits like seed size to wider patterns of plant community ecology.

Age is a significant contributing factor to the occurrence and progression of cardiovascular disease (CVD). Pharmacological treatment can effectively alleviate CVD symptoms caused by aging. However, 90% of the drugs have failed in clinics because of the loss of drug effects or the occurrence of the side effects. One of the reasons is the disparity between animal models used and the actual physiological levels in humans. Therefore, we integrated multiple datasets from single‐cell and bulk‐seq RNA‐sequencing data in rats, monkeys, and humans to identify genes and pathways with consistent/differential expression patterns across these three species. An approach called “Cross‐species signaling pathway analysis” was developed to select suitable animal models for drug screening. The effectiveness of this method was validated through the analysis of the pharmacological predictions of four known anti‐vascular aging drugs used in animal/clinical experiments. The effectiveness of drugs was consistently observed between the models and clinics when they targeted pathways with the same trend in our analysis. However, drugs might have exhibited adverse effects if they targeted pathways with opposite trends between the models and the clinics. Additionally, through our approach, we discovered four targets for anti‐vascular aging drugs, which were consistent with their pharmaceutical effects in literatures, showing the value of this approach. In the end, software was established to facilitate the use of “Cross‐species signaling pathway analysis.” In sum, our study suggests utilizing bioinformatics analysis based on disease characteristics can help in choosing more appropriate animal models.

Zebrafish have been found to be a premier model organism in biological and regeneration research. However, the comprehensive cell compositions and molecular dynamics during tissue regeneration in zebrafish remain poorly understood. Here, we utilized Microwell-seq to analyze more than 250,000 single cells covering major zebrafish cell types and constructed a systematic zebrafish cell landscape. We revealed single-cell compositions for 18 zebrafish tissue types covering both embryo and adult stages. Single-cell mapping of caudal fin regeneration revealed a unique characteristic of blastema population and key genetic regulation involved in zebrafish tissue repair. Overall, our single-cell datasets demonstrate the utility of zebrafish cell landscape resources in various fields of biological research.